Dabbling in Python with copilot (crawling, data visualization)

Copilot Chat will become more than just a simple AI assistant - it will be your reliable work secretary that maximizes your productivity and creativity. In this course, learn Copilot Chat's core features and usage methods, practical cases that can be applied immediately to real work, and customized tips tailored to each task, and start experiencing how your way of working changes with Copilot Chat!

Digital transformation (DX) is not a choice but a necessity. This course serves as the first step in digital transformation for all employees, providing easy and clear explanations from core DX concepts to business innovation cases. Don't fall behind in this changing era—develop the power to grow yourself and lead organizational innovation! Please don't overthink this lecture and take it with a light heart.

Understand Transformer-based LLM architectures and GPU utilization strategies, and gain hands-on experience with the actual serving process using vLLM. This course covers the entire practical workflow, from building AI system pipelines to monitoring and multi-GPU utilization, and is designed for intuitive understanding through diagrams and practice without complex formulas.

The online course “AI Teammates Do It All” is a hands-on program that teaches you how to use AI not merely as an automation tool, but as an “AI teammate” that works alongside you on practical tasks. The course is structured around common real-world workflows, including market research, proposal writing, strategy report creation, brand content visualization, project promotion and operations, and follow-up management. Participants assign various AI tools—including ChatGPT, Perplexity, Copilot, Canva, Gamma, MiriCanvas, and Vrew—as planning partners, strategic research partners, design partners, and operations support partners, and complete actual work deliverables with them. Across 30 sessions, you will learn step by step, from the basic mindset for working with AI to practical prompt writing, market research, proposal and report writing, brand content creation, and project operations. By following the course, you can develop the AI collaboration skills to work on your own like an entire team.

Conversation loops, tool calling, permissions, prompt assembly — learn the core principles of Claude Code by visualizing them through 3D interactive materials. Translate the structure you understood from the materials directly into code to complete your very own 'Mini Claude Code (Harness)'.

All lectures have been newly updated for June 2026, reflecting all the latest content. 5-Hour All-in-One Course → Apply directly to work with only the most essential services Practical AI Specialist Course → Step-by-step learning from sign-up to in-depth application Curated Essential AI for Work → Focus on core tools you actually use instead of 100 unused lectures Perfect Integration with Books → AI learning that can be utilized for a lifetime even without a textbook

This course teaches you how to build AI agents from scratch to a production-ready level using OpenClaw. Beyond a simple introduction to features, you will master OpenAI, local LLMs, memory, sessions, Tools, and Skills in a single, cohesive workflow. Based on hands-on experience and know-how gained from developing AI and large-scale systems in Silicon Valley, the course explains architectures and operational methods applicable to real-world projects. By the end of the course, you will be able to design your own AI agents and implement automation by integrating them with various services. This is a practice-oriented course for those who want to go beyond just using AI and learn how to build and operate it themselves.

Now, your AI is no longer in the cloud. It runs directly inside your laptop. Using LM Studio and Ollama, we will show you how to build a Private AI environment that runs entirely locally— from data processing and document analysis to code generation. Without security concerns, without costs, and even faster— Move beyond simply "using" AI and start "truly mastering" it.

Even those who have never experienced even the basics of coding can create automation software with just a few clicks. I'm serious.

This course is designed to teach the entire process of 'AI Training Data Construction,' which is essential for successfully executing AI modeling projects. Learners will not simply remain at the theoretical knowledge level, but will experience step-by-step the data construction processes required in actual practice. Specifically, the course covers the entire process from AI training data planning → acquisition → storage → preprocessing → labeling → pseudonymization and transformation through hands-on practice, structured to develop practical skills that can be immediately applied in the field. Additionally, learners will systematically study the most important data management capabilities in AI projects, such as data quality management and security issues, personal information de-identification processing, and dataset optimization. Through this, learners can grow from simple data collectors into data specialists who can proactively plan and execute AI projects. 👉 Through this course, learners will understand how to construct high-quality training data that determines AI model performance and acquire practical capabilities to effectively apply this in real work environments.

1. Python coding study to obtain the AI certification, AICE Associate 2. Step-by-step Python coding study from basics to applications 3. Lectures by Professor Joongheon Kim of Korea University, a scholar in the field of AI

WordPress Post Scheduling, Thumbnail Auto-Registration Program Code - Get Yours!

From PC control to high-level research and app development A guide to building your own 'AI Work Assistant' ready for immediate real-world deployment

Stop getting student-record planning. I’ll reveal the entire consulting playbook used by a college admissions consultant with 30 years of experience.

An AI that understands Korean well, handles long documents, and even carries out real-world tasks—that is exactly the direction Solar Open 2 is aiming for. This class provides an accessible explanation of Upstage’s Solar Open 2 technical report in the order of “Introduction → Design → Training → Evaluation.” Technical terms are explained through everyday analogies and visual materials, enabling even beginners to understand “what,” “how,” and “why” as one coherent flow.

Learn how to structure diverse data—including students’ grades, school records, and areas of interest—using the AI-SPARS tool, and leverage an LLM to design everything from major exploration and college/admissions strategies to personalized roadmaps. Rather than simple Q&A, you can immediately apply in practice a systematic AX-style career and college counseling process that progresses from Profile-Interview-Major-College-Admissions Track-Gap-Roadmap-Smart Report-Portfolio.

Automate YouTube Shorts creation with AI!! Learn how to automatically create YouTube Shorts using n8n from scratch. We will personally build a workflow that handles everything at once: Text → Image/Music → Video Creation → Uploading. Practice includes distinguishing between test/production modes and tips for saving costs. By the end of the lecture, you will complete 3 automation templates that can be used immediately. We will learn step-by-step, starting from node placement, so you can follow along even without coding knowledge. Join us in automating AI YouTube Shorts production!

This is a course on creating blog images using DALL-E 3. This course provides practical knowledge and hands-on opportunities from the basics of image generation technology to advanced usage techniques and problem-solving strategies.

This course is designed to prepare you for the Information Processing Engineer practical exam solely through solving previous exam questions. Instead of unnecessary theories or vast amounts of content, it focuses on past exam questions that are repeatedly featured, allowing you to connect your learning directly to passing the exam. You can quickly grasp core points and question patterns by reflecting on the latest trends, and even learn tips for writing answers through the problem-solving process. This lecture is optimized for examinees aiming to pass efficiently in a short period of time.

As the digital transformation of the manufacturing industry accelerates, production facilities, control systems, and industrial networks are becoming increasingly connected to external systems. Along with this, the possibility of cyberattacks leading to production shutdowns, quality degradation, technology leaks, and safety accidents is also growing. The [OT (Manufacturing) Security] Master Class for 4 Major Manufacturing Industries is a course that examines OT security threats that can occur in the automotive, semiconductor, chemical, and food/pharmaceutical industries, focusing on real-world manufacturing site cases. Participants will understand how production processes and facility environments differ across each industry and systematically learn about key security threats, causes of accidents, and response strategies specific to each sector. The course covers a wide range of topics in a single program, including smart factory and supply chain security in the automotive industry, protection of core processes and technical information in the semiconductor industry, control systems and safety accident response in the chemical industry, and quality, hygiene, and GMP data protection in the food and pharmaceutical industries. Rather than simply listing complex technologies or attack techniques, the course explains "what problems can occur," "why they occur," and "how to respond on-site" in a way that is easy for even beginners to understand. Through this lecture, you can compare the characteristics of the four major manufacturing industries and the differences in OT security, and learn the basic direction of security inspections and accident response required at manufacturing sites.